A Knee-Point Driven Multi-Objective Evolutionary Algorithm For Flexible Job Shop Scheduling

Job shop scheduling or the job-shop problem (JSP) is an optimization problem that has been studied on many industrial manufactures. For a certain problem in the real world with more than one objectives, it's hard for decisionmakers to select a certain solution from the well-shaped Pareto Front because the number of solutions could be huge. Thus, obtaining a certain solution or a set of solutions that satisfied the decision-maker most is of significant importance. Knee points are solutions with maximum marginal rates of return on the Pareto Front, which are considered as better options if there are no other preference. This paper proposed a knee-point-driven multi-objective algorithm to solve the flexible job shop scheduling problem (FJSP). Experimental results show that the proposed method can not only obtain better results but also help decrease the selecting pressure for decision-makers compared to traditional NSGA-II.